Tongliang Liu


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Tongliang Liu

Tongliang Liu

Lecturer (Assistant Professor) in Machine Learning
School of Computer Science
Facult of Engineering
The University of Sydney

Address: Room 315/J12/ 1 Cleveland St, Darlington, NSW 2008, Australia
E-mail: tliang.liu [at] gmail.com; tongliang.liu [at] sydney.edu.au
[Google Scholar] [DBLP]

Greetings! I am currently a Lecturer with the School of Computer Science at The University of Sydney. Before joining USyd, I was a Lecturer with the Centre for Artificial Intelligence at the University of Technology Sydney.

I am always looking for highly-motivated students to join our group. If you are interested in the research in our group, please send an email to tongliang.liu@sydney.edu.au about your interests and background (attaching your CV, transcripts, and any previous research papers). Thanks!

A few visiting positions in machine learning and computer vision are available.

Some information about scholarships:

  • For both domestic and international PhD students, you can apply for the RTP scholarship or the Faculty scholarship. There is no specific deadline for the application. I would help you assess the probability to get a scholarship.
  • For international PhD students, you can also consider applying for some general scholarships . There are strict deadlines for the scholarships. For example, the CSC-USYD scholarship has a deadline normally in December.
  • For all students, there are also many other scholarships to explore. I am happy to supervise outstanding students who can get scholarships.

  • Research Interests

    My research interests lie in providing mathematical and theoretical foundations to justify and understand machine learning models and designing efficient learning algorithms for problems in computer vision and data mining, with a particular emphasis on
    • Statistical learning theory (e.g., hypothesis complexity and generalisation error)

    • Weakly supervised learning (e.g., transfer learning, learning with label noise, positive and unlabeled learning)

    • Adversarial learning (e.g., adversarial attack and defense)

    • Unsupervised learning (e.g., clustering and matrix factorisation)

    • Image and video processing (e.g., classification)


    News

    • 11/2019, two papers have been accepted by AAAI.

    • 11/2019, a paper has been accepted by IEEE TCYB.

    • 10/2019, I accepted the invitation to serve as an SPC for IJCAI 2020.

    • 10/2019, a paper has been accepted by IEEE TPAMI.

    • 09/2019, a paper has been accepted by IEEE TPAMI.

    • 09/2019, two papers have been accepted by NeurIPS 2019.

    • 08/2019, a paper has been accepted by IEEE TNNLS.

    • 08/2019, I accepted the invitation to serve as a PC for AISTATS 2020.

    • 07/2019, we have been awarded the ICME Best Paper Award.

    • 07/2019, a paper has been accepted by IEEE TNNLS.

    • 06/2019, I accepted the invitation to serve as an SPC for AAAI 2020.

    • 05/2019, a paper has been accepted by IEEE TIP.

    • 05/2019, a paper has been accepted by IJCAI.

    See more previous news here.


    Selelcted Publications

    See the full list here.